1. Field of the Invention
The present invention relates to a method and apparatus for inspecting a substrate. More particularly, the present invention relates to a method of inspecting a substrate to detect defects on the substrate such as particles or distortions of minute structures, and an apparatus for performing the method.
2. Description of the Related Art
To process large amounts of data in a relatively short time, semiconductor devices are generally highly integrated having a large capacity for the data. During their manufacturing, these semiconductor devices are susceptible to defects such as particles, bridges and sinks. Further, after a chemical mechanical polishing (CMP) process is carried out, defects such as scratches may be generated on a surface of the semiconductor substrate. Thus, an inspection process to determine the presence of defects is an important aspect of the devices' production. And as these semiconductor devices become even more highly integrated, the inspection process becomes more important, but at the same time the inspection for defects becomes more difficult to be accurate. Defect-Inspecting apparatuses are classified as either an optical inspection apparatus that uses a light source or an image-inspecting apparatus that uses a microscope.
An example of a method of inspecting defects using an optical inspection apparatus and a method of manufacturing a semiconductor device is disclosed in Japanese Patent Laid-Open Publication No. 2003-270168 (filed by SEIKO EPSON CORP., Sep. 25, 2003). According to the above Japanese Patent, to reduce defect detection errors caused by spots such as a watermark on a semiconductor substrate, values of brightness of a number of inspection regions are averaged to calculate a reference brightness of all the inspection regions.
An image-inspecting apparatus mainly uses a scanning electron microscope (SEM). A method of inspecting defects using the SEM is classified as either a single frame-comparing type apparatus or a golden image-comparing type apparatus.
According to the single frame-comparing type apparatus, an image of an inspection region is compared with an image of an adjacent inspection region to recognize whether there are defects in the inspection region. However, if similar defects are in the adjacent inspection region as well as the inspection region, these defects may be difficult to detect. To overcome the above-mentioned problem of the single frame-comparing type method, the golden image-comparing type method is proposed.
The golden image-comparing type method utilizes images of a plurality of regions on which minute structures substantially similar to those on an inspection region are formed. These images are added to or subtracted from one another to obtain a golden image. The golden image is compared with an image of the inspection region to recognize whether defects exist in the inspection region. Although the golden image-comparing type method has good detection accuracy compared to that of the single frame-comparing type method, there is a problem, however, in that noise is included in the golden image. Particularly, a minute structure on a central portion of a semiconductor substrate has characteristics different from that on a peripheral portion of the semiconductor substrate. This is caused by a non-planarized surface of the semiconductor substrate and a non-simultaneous formation of the minute structures.
FIG. 1 is a picture illustrating an image of an inspection region obtained using a conventional method of inspecting a substrate, and FIG. 2 is a picture illustrating a golden image obtained using the conventional method of inspecting a substrate.
Referring to FIGS. 1 and 2, when the image 10 of the inspection region is compared with the golden image 20, it can be noted that noise is included in the golden image 20. Although the noise has a relatively low intensity, it may be detected as defects when a set threshold has a low value by subtracting the image 10 of the inspection region from the golden image. Thus, to minimize an influence of the noise, the threshold should be set at a high value. However, when the high threshold is set, it may be higher than an intensity of a signal with respect to actual defects on the inspection region. As a result, the signal with respect to the actual defects on the inspection region is regarded as a signal lower than the threshold so that the actual defects are not detected. Therefore, there is a restriction on setting the high threshold.
Because a semiconductor device is highly integrated, the number of defects that may be detected on a single semiconductor substrate has increased to the thousands. Needless to say, these defects greatly influence many of the semiconductor processes.
Because of the importance of defects and their effects on semiconductors, there is an ever-growing need for improved methods and apparatuses for detecting defects.